736 research outputs found

    Archetypal Analysis: Mining Weather and Climate Extremes

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    Conventional analysis methods in weather and climate science (e.g., EOF analysis) exhibit a number of drawbacks including scaling and mixing. These methods focus mostly on the bulk of the probability distribution of the system in state space and overlook its tail. This paper explores a different method, the archetypal analysis (AA), which focuses precisely on the extremes. AA seeks to approximate the convex hull of the data in state space by finding “corners” that represent “pure” types or archetypes through computing mixture weight matrices. The method is quite new in climate science, although it has been around for about two decades in pattern recognition. It encompasses, in particular, the virtues of EOFs and clustering. The method is presented along with a new manifold-based optimization algorithm that optimizes for the weights simultaneously, unlike the conventional multistep algorithm based on the alternating constrained least squares. The paper discusses the numerical solution and then applies it to the monthly sea surface temperature (SST) from HadISST and to the Asian summer monsoon (ASM) using sea level pressure (SLP) from ERA-40 over the Asian monsoon region. The application to SST reveals, in particular, three archetypes, namely, El Niño, La Niña, and a third pattern representing the western boundary currents. The latter archetype shows a particular trend in the last few decades. The application to the ASM SLP anomalies yields archetypes that are consistent with the ASM regimes found in the literature. Merits and weaknesses of the method along with possible future development are also discussed

    Predictability and Non-Gaussian Characteristics of the North Atlantic Oscillation

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    AbstractThe North Atlantic Oscillation (NAO) is the dominant mode of climate variability over the North Atlantic basin and has a significant impact on seasonal climate and surface weather conditions. It is the result of complex and nonlinear interactions between many spatiotemporal scales. Here, the authors study the statistical properties of two time series of the daily NAO index. Previous NAO modeling attempts only considered Gaussian noise, which can be inconsistent with the system complexity. Here, it is found that an autoregressive model with non-Gaussian noise provides a better fit to the time series. This result holds also when considering time series for the four seasons separately. The usefulness of the proposed model is evaluated by means of an investigation of its forecast skill

    Wastewater reuse in agriculture in the outskirts of the city Batna (Algeria)

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    The study is based on a survey of farmers. The data collected allow us to understand the reasons for the reuse of wastewater. This resource can be an important element in irrigation water management strategy. The possibilities of wastewater reuse in agriculture are significant, as is the case in the Batna region. In this context, the presence of texts establishing the modality of wastewater reuse, are a prerequisite for promotion of wastewater reuse projects. Policymakers are faced with the need to exploit the increase in volumes to meet greater demand. To do this, the integrated management should be considered now as a public / private partnership model and as the best approach for development and efficient and sustainable management.Keywords: Farmers, Irrigation, Management, Public Policy, Text

    Analysis of the phenotypic variability of twenty f3 biparental populations of bread wheat (Triticum aestivum L.) evaluated under semi-arid environment

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    This research was conducted to screen and analyse the variability within twenty F3 populations of bread wheat (Triticum aestivum L.) generated by Line x Tester mating design. The results indicated the presence of sufficient variability within and between F3 populations for the eight measured variables, which represent plant phenology, physiology, yield and yield components. Different populations have been identified to improve the measured variables separately. The number of spikes appeared to be the most important determinant of grain yield. PCA and cluster analyses indicated that the Acsad1069/El Wifak and Acsad1135/Hidhab, with a relatively high grain yield,  aboveground biomass and 1000 grains weight, are the best F3 populations to improve the productivity. However, Acsad899/Rmada and Acsad1135/Rmada populations were earlier and had a low number of spikes. These populations had also favorable genes for heat tolerance.Keywords: Triticum aestivum L.; Variability; Selection; Tolerance; Yield

    Impeller optimization in crossflow hydraulic turbines

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    Crossflow turbines represent a valuable choice for energy recovery in aqueducts, due to their constructive simplicity and good efficiency under variable head jump conditions. Several experimental and numerical studies concerning the optimal design of crossflow hydraulic turbines have already been proposed, but all of them assume that structural safety is fully compatible with the sought after geometry. We show first, with reference to a specific study case, that the geometry of the most efficient impeller would lead shortly, using blades with a traditional circular profile made with standard material, to their mechanical failure. A methodology for fully coupled fluid dynamic and mechanical optimization of the blade cross-section is then proposed. The methodology assumes a linear variation of the curvature of the blade external surface, along with an iterative use of two-dimensional (2D) computational fluid dynamic (CFD) and 3D structural finite element method (FEM) simulations. The proposed methodology was applied to the design of a power recovery system (PRS) turbine already installed in an operating water transport network and was finally validated with a fully 3D CFD simulation coupled with a 3D FEM structural analysis of the entire impeller
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